Methods and software for self-gating a set of images

ABSTRACT

Methods and software for self-gating a set of images. In exemplary embodiments, a fundamental heart frequency of the patient can be measured without the use of an ECG signal. In one method, the fundamental heart frequency can be determined by analyzing the size of the heart in the images. In another method, the fundamental heart frequency can be determined by applying a Fourier Transform. The measured fundamental heart frequency can thereafter be used to select slice images from the image scan for creation of a sagittal or coronal projection image. In exemplary embodiments, the resultant projection image can be used for coronary calcium detection and scoring.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application claims benefit to U.S. Provisional PatentApplication Ser. No. 60/306,311 filed July 17, 2001, the completedisclosure of which is incorporated herein by reference.

The present application is also related to U.S. patent application Ser.No. 10/159/816 entitled “Graphical User Interfaces and Methods forRetrospectively Gating a Set of Images,” filed herewith, and U.S. patentapplication Ser. No. 10/159,814 entitled “Methods and Software forRetrospectively Gating a Set of Images,” also filed herewith, thecomplete disclosures of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

The present invention relates generally to medical imaging. Morespecifically, the present invention relates to gating of an image scanto improve calcium scoring of a patient's heart and coronary arteries.

CT scanning of the heart is an increasingly common procedure to obtaininformation about the presence of calcification in the coronaryarteries. Unfortunately, two body motions can interfere with the qualityof the images obtained by the CT scanner: the heart motion and thepatient's breathing motion. A normal heart scan takes about 20 secondsand to reduce the effect of the breathing motion, the patient isgenerally asked to hold their breath to eliminate the breath motion. Theheart motion, on the other hand, cannot be readily eliminated and canlead to blurring, introduction of artifacts into the images, andmisregistration.

A common procedure to reduce the heart motion is gating. As is describedin U.S. Pat. Nos. 6,370,217 B1 and 6,243,437 to Hu et al., the motion ofthe heart is fastest during systole and relatively motionless duringdiastole. Prospective gating methodologies use an electrocardiographsignal (ECG) to predict the time of the diastole such that the CTscanner can be activated to obtain an image during the relativelymotionless diastole period. A major issue with prospective gating insubjects with irregular heart beats is that the trigger can only be setto acquire data after the R-wave. If the following beat is short, thedata acquisition may overlap the next systolic period. Retrospectivegating, on the other hand, uses the electrocardiograph signal toretrospectively find motionless points in the heart cycle to select theimage slice. In retrospective gating, the ECG signal information can beused, in retrospect, to select the slice images that were acquiredduring the diastole. The heart moves through a cycle in somewhat under asecond, and a scanners generally take from a quarter second to a halfsecond to acquire the information for each slice, thus it is possible toselect from a number of slices for each cardiac cycle.

There are two major issues with retrospective gating. The first is thatwhile reconstruction at finer intervals than the whole acquisition cycledoes not increase the radiation dose to the subject to produce the extraimages, the overlap of the scanned volume and the fact that thescanner's x-ray tube is continuously on (instead of being turned offduring the parts of the cardiac cycle that are not of interest) increasethe radiation dosage. The second problem is that gating from an ECGsignal requires the placement of electrodes on the subject and testingto confirm that their placement is adequate. In a busy screening ordiagnostic practice the added steps can decrease utilization andnegatively affect the economics of the imaging operation.

There are various shortcomings in existing software for retrospectivegating. When the operator is performing the selection of slices, thereis no real time feedback as to the adequacy of the selection.Information as to the length of the cardiac cycle during the study,convenient ways to ascertain whether it changed during the study, andmeasurement of any one cycle are also not readily available. Except formanually adjusting each slice (there can be 350–500 slices in a study),there is no way to account for changes in the cardiac cycle. All ofthese contribute to decreasing the certainty with which a particularcoronary calcium score is known, and to increasing the variability ofthe resulting calcium scores.

Consequently, what is needed are improved methods and software forgenerating a reconstructed projection image of the patient's heart whichmore fully utilizes the information content of the acquisition cycle, sothat less of the increased dose is wasted or thrown out. Additionally,what is also needed are methods and software that can gate an image scanwithout the use of an ECG signal.

BRIEF SUMMARY OF THE INVENTION

The present invention provides methods and software for improving theimaging of a patient's heart. In a particular use, the present inventionimproves calcium scoring and 3-D rendering of a patient's heart bygating a set of images without the use of a gating signal.Advantageously, the methods of the present invention use informationpresent in the slice images themselves to select slices for calciumscoring and 3-D rendering.

Typically, the images are analyzed to calculate a fundamental heartfrequency, and projection images are generated by selecting slice imagesthat were obtained during the same specific point (typically diastole)of the patient's cardiac cycle. The selected images can thereafter becalcium scored, if desired.

In one aspect, the present invention selects slice images from the setof slices based on the size of the heart. A set of overlapping images ofthe volume of the patient is acquired. Selection of the images can bedone successively by depopulating the slice set (based on the size ofthe heart in the image) until the necessary number of slice images areselected, enough to cover the heart without gaps, which depends on slicethickness and heart size. In one exemplary embodiment, depopulating theimage scan can be carried out by pairwise comparison. Once the sliceimages are selected, the coronal/sagittal projection can be generatedand the selected images of the heart can be calcium scored or 3-Drendered.

In another aspect, the present invention comprises generating aplurality of sagittal or coronal projection images of the patient'sheart. Each projection image will include groups of slice images of thepatient's heart that were taken during the same phase of the patient'sheart frequency. Consequently, a projection image can be displayed ofthe patient's heart during each of the phases of the patient's heartbeat (e.g. systole, diastole, and the like.) Thereafter, a user candetermine which slice sets are best for calcium scoring or 3-D renderingbased on the projection images.

In an exemplary method, a set of overlapping slice images of a patient'sheart is acquired. A coronal or sagittal projection with the set ofslice images is generated and a region of the projection is marked. Themarked region is analyzed to calculate a heart frequency and phase ofthe patient's heart motion. Groups of slice images are selected from theset of slice images, based on their relative position in the calculatedheart motion frequency and phase. Thereafter, a plurality of groups ofslices are generated that correspond to different phases of the heartmotion.

In some embodiments, the marked region is analyzed by applying at leastone of a Fourier transformation and a derivative filter to an intensitysignal that is derived from the slice images. The Fourier transform canbe used to derive a fundamental heart frequency, while the derivativefilter can be used to measure the phase of each of the slice images soas to allow the user to determine which slices correspond to thepatient's diastole.

In some configurations, the methods and software of the presentinvention can apply a quality measure to the plurality of groups ofslices to rank the images. Typically, the images will be ranked on thesize of the marked region of the heart in the projection of the slices,since the heart is largest (and clearest) when the heart is in diastole.

In another aspect, the present invention comprises determining afundamental heart frequency of the patient by applying a Fouriertransformation to an intensity signal of the image slices. A pluralityof overlapping slice images of a patient's heart can be obtained. Acoronal or sagittal projection is generated with the set of sliceimages. The invention of this application is not limited to the use ofcoronal or sagittal projections. Other projections may be chosen, suchas those of the heart's short or long axis. A region of the projectionimage is marked and an intensity signal of the marked overlapping sliceregion is calculated along each line in the projection imagecorresponding to a slice. The intensity signal can be Fouriertransformed to find a fundamental frequency of the patient's heartcycle. The intensity signal can be analyzed with a derivative filter tolocate slice images that were obtained during the diastolic portion ofthe patient's heart cycle. The intensity signal analysis can be furtherused to establish a phase of the fundamental frequency obtained from theFourier transformation of the heart motion. The selection process can beextended outside the marked region by obtaining the frequency of theheart motion from the Fourier transformation and the phase from theintensity signal, and slices can be selected that correspond to thepatient's diastole. Optionally, the selected slices can thereafter becalcium scored and/or 3-D rendered.

In yet another aspect, the present invention provides a method ofFourier gating an image dataset. The method comprises obtaining aplurality of overlapping slice images of a patient's heart. A coronal orsagittal projection is generated with the set of slice images. A regionof the projection image is marked and an intensity signal of the markedoverlapping slice region is calculated along each line in the projectionimage corresponding to a slice. The intensity signal can be Fouriertransformed to find a fundamental frequency of the patient's heartcycle. A principal component of the Fourier spectrum is obtained withinan allowed frequency window. Data sets of slices are formed in which thedatasets are separated by a time interval that substantially correspondsto the time interval corresponding to the principal component. Aprojection image formed from the data sets is presented to the operatorto select a set for further processing. Optionally, the selected slicescan thereafter be calcium scored and/or 3-D rendered.

For a further understanding of the nature and advantages of theinvention, reference should be made to the following description takenin conjunction with the accompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically illustrates a simplified retrospective gatingmethod of the present invention with the optional steps in dotted lines;

FIG. 2 illustrates one exemplary graphical user interface displayinginformation regarding the duration of an R—R cycle of a patient;

FIG. 3 is an enlarged portion of the R—R cycle information of FIG. 2;

FIG. 4 illustrates a graphical user interface having the view tab andview screen displayed and slice images selected during a diastole;

FIG. 5 illustrates a graphical user interface displaying slice imagesselected during a systole;

FIG. 6 is a graphical user interface displaying a stretched image and anoverlaid ECG signal;

FIG. 7 schematically illustrates a simplified method of self gating aset of image slices;

FIG. 8 schematically illustrates another simplified method of selfgating as et of image slices with the optional steps in dotted lines;

FIGS. 9A and 9B are coronal and sagittal projections of a patient'sheart, respectively;

FIG. 10 illustrates a freehand editing of a region of interest;

FIG. 11 illustrates a straight line editing of a region of interest;

FIG. 12 is an example of an intensity profile;

FIG. 13 is a smoothed output of a local intensity signal with markersindicating maxima obtained from a derivative filter;

FIG. 14 is an example of a power spectrum;

FIG. 15 illustrates a graphical user interface in which an ECG has notbeen loaded and a user can self-gate the image scan;

FIG. 16 is an exemplary data flow diagram of self gating; and

FIG. 17 is a graphical user interface of a self gating preview.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides methods and graphical user interfaces forself gating and retrospectively gating a set of image slices (referredto herein as an image scan).

While the remaining discussion focuses on the gating of an image scanfrom a CT scanner for use in coronary calcium measurements, it should beappreciated that the methods and devices of the present invention arenot limited to such imaging modalities and uses. For example, instead ofanalyzing the image scan for measuring coronary calcium, the image scancan be used for 3-D reconstructions of the heart, such as those used forCT angiography, or for heart function studies, including dynamicstudies.

In some exemplary embodiments, the present invention uses a patient'smeasured ECG signals taken during the acquisition of the image scan togate the image scan. The ECG signal is a repetitive pattern thatreflects the electrical activity of the patient's heart. An ECG signalhas a plurality of cardiac cycles (sometimes referred to as R—R cycles),with each cardiac cycle beginning with an R-wave (e.g., highestamplitude peak) during systole and ending with a relatively motionlessdiastolic phase . Blurring of the images is most likely to occur whenimaging during systole. Consequently, it is preferable to use imageslices taken during diastole so as to reduce the amount of artifactsfound in the selected image(s).

Unfortunately, the R—R interval can vary through the image scan and thecardiac cycle will not always occur during regular intervals (e.g.,irregular heartbeat). For example, in many imaging sessions, the subjectis asked to hold their breath so as to reduce introduction of artifactsdue to the breathing motion. The patient's holding of their breath,however, may cause a change in the heart cycle. Additionally, patient'swho have irregular heart beats may not be effectively imaged byselecting a specific point in time during the cardiac cycle. While somestudies have proclaimed that it is best to select a particular time withrespect to the R-wave, (some preferring a certain number of millisecondsbefore or after the R-wave), the selection of an absolute time does notallow for compensation for irregular heartbeats or changing timesbetween successive R-waves.

FIG. 1 schematically illustrates one method 20 of the present invention.First, a set of slice images of a volume of tissue of the patient isobtained and a coronal or sagittal reconstruction of the slice imagescan be generated. (Step 22). Acquisition of the image scan can becarried out by any conventional or proprietary CT scanner (e.g., moving,stationary, single detector, multiple detector, helical, and the like).A helical scan of the heart can include approximately 350–500overlapping images, while a non-overlapping scan usually includes around40–50 slices. It should be appreciated however, that it may be possibleto use magnetic resonance image (MRI) scanners, ultrasound scanners, orother slice imaging devices to obtain the image scan used in the methodsof the present invention.

The electrical activity of the patient's heart can be measured byattaching one or more electrocardiograph leads to the patient to monitorthe patient's ECG signal during the acquisition of the image scan. Theelectrical activity can be analyzed to derive information regarding theduration of each of the R—R cycles of the ECG signal (Step 24). The R—Rcycle information allows the user to determine if there are anysubstantial variations in the duration of the R—R cycles over theacquisition period of the slice images. Such information allows the userto make appropriate adjustments to their selection of the slice imagesused for generating the coronal/sagittal projection, for calciumscoring, or for 3-D rendering.

The ECG information can be analyzed automatically by software ormanually by the user to determine the duration of each cardiac cycle(illustrated in FIGS. 2 and 3 as “Duration of R-Cycle”). Based on thecalculated R—R cycle information, the user can choose an appropriateglobal selection criteria of choosing the slice images from the imagescan (Step 26). In exemplary embodiments, the selection criteria forchoosing the slice image(s) includes (1) an absolute time period beforeor after the R-wave or (2) a percentage of the cycle (e.g., 65% of theheart cycle) before or after the R-wave. In exemplary embodiments, theuser will be allowed to separately choose the selection criteria (e.g.,percentage or absolute time) and a timing selection (e.g., before orafter the R-wave).

It should be appreciated however, that while the preferred selectioncriteria are an absolute time before or after the R-wave or a percentageof the cardiac cycle before or after the R-wave, that other selectioncriteria may be used to select the slice images.

In some embodiments, when the user selects a percentage of the cycle asthe selection criteria, the software of the present invention can alsodisplay a complementary time value that corresponds to the selectedpercentage. Similarly, if a user chooses an absolute time period, thesoftware of the present invention can display the correspondingpercentage. This significantly decreases operator load. For instance,for most of the heart cycles, the heart rate may be quite constant. Theoperator can set a preferred time, say, 450 msec before the R-wave, andthe program will show what percentage of the cycle this is. The operatorcan then select for a portion of the scan when the heart rate slows nearthe end, a percentage that is already available from the software. Inanother case the heart rate may have increased, and the end of the scanmay overlap the following R-wave. The operator can then select thecomplementary time after the R-wave to better center the selected image.

In exemplary embodiments, a graphical illustration of the duration ofthe R—R cycle can be displayed on a user interface to illustrate theduration of the R—R cycle. Advantageously, the graph of the R—R cyclewill guide the user toward the patient's irregular heart beats and showif there are any substantial variations in the length of the R—R cyclethat may effect the selection of the slices.

One example of a graphical illustration is illustrated in FIG. 3. Graph92 shows that the duration of the R—R cycle is substantially the samelength during the entire acquisition period. Graph 94 (in dotted lines)shows that the duration of the R—R cycle changes over the acquisitionperiod.

In the instance in which graph 92 is relatively consistent over time,the user can apply an absolute time period (before or after the R-wave)to select the slice images for inclusion in the reconstructionprojection image. Since the R—R cycles are substantially the samethroughout the acquisition period, the absolute time period shouldgenerally fit each of the R—R cycles.

If the duration of the R—R cycle changes over the acquisition period(shown as a dotted line 94), the user would likely use the “percentageof cardiac cycle” (before or after the R-wave) selection criteria toselect the slices since the absolute time does not compensate forirregular or changing times of the R—R cycle. While an absolute timeperiod, (for example 450 msec before the R-wave) may be appropriate fora first portion of the ECG signal, because the R—R cycle decreases overtime, the chosen absolute time period would likely be inappropriate forthe latter, shorter R—R cycles since the selected slice would likelyoverlap over a portion of the high amplitude R-wave. Thus, such a slicewould likely introduce artifacts into the resultant projection image andreduce the accuracy of the calcium scoring of the image slice.

Additionally or alternatively, to graphically illustrate the duration ofthe R—R cycle, the methods of the present invention can also numericallydisplay the duration of the R—R cycle for specific intervals of theacquisition period of the ECG. For example, as illustrated in FIG. 3,the acquisition period may be broken up into a plurality of intervals.In one exemplary embodiment, the first interval 104 is the first 10cycles of ECG, the second interval 106 is the middle 10 cycles of theECG, and the third interval 108 is the last 10 cycles of the ECG. Itshould be appreciated however, that the ECG can be separate into anynumber of different ECG intervals, and the present invention should notbe limited to the illustrated three intervals.

By quantitatively providing the average length of the R—R cycle for thedifferent intervals, the user will be able to accurately determine whichselection criteria to employ. For example, if the R—R cycle durationvaries by more than a certain percentage or time length (typically about70 msec or about 10% of the R—R cycle), the user will likely want toemploy the percentage selection criteria. But if the R—R cycle durationdifference is less than the certain percentage or time length, the userwill likely want to employ the absolute difference criteria, asdescribed above.

Alternatively, instead of choosing a global absolute time period for allof the cycles, it may be possible to apply a separate selection criteriato each of the intervals of the ECG. Thus, if two of the intervals areconsistent and the third interval is changing in duration or at a lowerduration than the first two intervals, it may be beneficial to apply anabsolute time selection criteria to the first two intervals and ashorter absolute time duration or a percentage of cycle to the thirdinterval. For example, for the illustrated example in FIG. 3, as firstattempt, the user can select a slice image that is 450 msec before theR-wave for first 10 cycles, 450 msec before the R-wave for middle 10cycles, and 400 msec before the R-wave for last 10 cycles. In thismanner, an optimal selection can be achieved, the possibilities beinglimited by the acquisition process, and not the gating software.

After the appropriate selection method is chosen and applied, theselected slices will be combined to generate a correctedcoronal/sagittal projection. (Step 28). In some embodiments a bilinearalgorithm is used to generate the correct aspect ratio coronal/sagittalprojection. It should be appreciated however, that other conventionalinterpolation and scaling algorithms can be used.

The combination of functionalities and flexibility in choosing theslices allow for convenient and at the same time highly specificselection of slices on the basis of timing with respect to the ECGsignal. Because the selection of the slices can be displayed to the userin real time (described below), the user can rapidly assess the adequacyof the timing selection of the slice images.

If the projection images are deemed to be acceptable, the selectedslices can be calcium scored or 3-D rendered, if desired. (Step 32).Because there is an overlap of the slices during scanning, and becausethe x-ray tube is on during the full cardiac cycle instead of justduring the acquisition of the desired time interval within the cycle (asin prospective gating) there is an increase in delivered radiation doseto the patient. Such a dosage increase in unavoidable, butretrospectively it is possible to obtain information from the additionalradiation dose. After acquisition, the reconstruction software cangenerate additional slices at finer intervals than those determined bytable motion and scanner rotation speed, typically ten times finer. Inmethods which analyze the slice images for calcium scoring, the calciumwill be very bright in the images. Using a maximum intensity projectionalgorithm, the selected slice and its two immediate neighbors can beanalyzed to select the brightest pixel in each of the slices. The slicethat has the brightest pixel can then be chosen for inclusion in thecalcium scoring study. Thus, the process of the present inventioneffectively utilizes three out of ten images (e.g., the “selected” sliceand its two neighbors) instead of just one out of every ten images.

Because a CT image is obtained from hundreds of individual projectionsand processed through back-projection algorithms, inconsistencies insome projections due to heart motion or motion of a point in the heartthat in some way aliases with the acquisition process can produce asignificant artifact even at a time where the heart is relativelyquiescent. Optionally, if the selected slice images chosen by the abovemethod are not all deemed appropriate because of such a problem, theuser can manually scroll through the selected slice images and chooseother “non-selected” slice images to replace the undesired “selected”slice images. (Step 30). One method of deselecting slices from the imagescan is described below, in relation to one exemplary graphical userinterface of the present invention.

FIGS. 2–6 illustrate some exemplary graphical user interfaces andmethods for gating an image scan. It should be appreciated however, thatthe graphical user interfaces described and illustrated herein are meantonly to be examples, and should not be used to limit the scope of thepresent invention.

FIG. 2 schematically illustrates one exemplary graphical user interface(GUI) 40 of the present invention. GUI 40 is generally displayed on auser output device such as a computer monitor. GUI includes a firstscreen portion 42 for displaying a selected image, a second screenportion 44 for displaying an ECG that was taken during the image scan,and a third screen portion 46 for displaying a coronal and/or a sagittalimage projection of the selected slices. Typically, third screen portion46 will display a first projection image 48 that is composed of all ofthe slices of the image scan and/or a second projection image 50 that iscomposed only of the selected images slices. As will be described indetail below, GUI can further include a fourth screen portion 52 thatcan be toggled between a variety of views to allow a user to select anddisplay various functions, menus, and information. GUI can also includea menu toolbar 53 so as to allow a user to select and toggle between thedifferent functionalities and plug-ins of the software of the presentinvention.

In preferred embodiments the GUI 40 of the present invention cansimultaneously display on a single screen a selected slice image, atleast a portion of the ECG signal, and the sagittal/coronalreconstruction projection image that is composed of the selected slices.Such an interface 40 allows the user to view in real-time, the effectthat the choice or change of image slices has on the quality andresolution of the composite projection image. Thus, if the selectedslices do not improve the quality of the coronal or sagittalreconstruction projection image, the user can de-select the slice(s) toimprove the image quality, and hence improve the calcium scoring or 3-Drendering of the patient's heart.

As shown in FIG. 2 in exemplary embodiments first screen portion 42 candisplay a selected slice image in window 54 and previous and next sliceimages in windows 56, 58, respectively. Slice image window 54 caninclude a header 60 that indicates the slice number, zoom level, and thelike. The adjacent slice image windows 56, 58 can include a header thatindicates “Previous Slice” or “Next Slice.” It should be appreciatedhowever, that a variety of headers can be used to indicate otherinformation, if desired. Image windows 56, 58 can include a scroll bar61 that allows a user to scroll through (review) the slice. In someexemplary embodiments, image windows 56, 58 that display thenon-selected slices are smaller in size than image window 54. It shouldbe appreciated however, that if desired, image windows 56, 58 can be thesame size or larger than image window 54 if desired.

First screen portion 42 can also include user actuatable buttons 62, 63that allows the user to toggle through the other individual slice imagesof the image scan. If user actuates button 63, the image slice that wasoriginally displayed in window 58 will be displayed in window 54, theimage slice that was originally displayed in window 54 will be moved toimage window 56, the image originally displayed in image window 56 willnot be displayed, and a previously undisplayed slice image will be shownin window 58. Likewise, if a user actuates button 62, the image slicethat was originally displayed in window 56 will be displayed in window54, the image slice that was originally displayed in window 54 will bemoved to image window 58, the image originally displayed in image window58 will not be displayed, and a previously undisplayed slice image willbe displayed in window 56.

As shown in FIG. 4, if the slice image displayed in window 54 is not a“selected slice,” first screen portion 42 can include a “Select Slice”button 64 that allows the user to select a previously “unselected” slicethat is displayed in window 54 for inclusion into the projection imagedisplayed in third screen portion 46. Similarly, if a slice displayed inwindow 54 is a slice that is already selected or included in projectionimage 50, first portion 42 can include a “Deselect” button 65 that, whenactuated, can remove the slice from inclusion in the reconstructionprojection image. (FIG. 2)

If through any of the process described therein, there are gaps in theimage data, before saving or calcium scoring the gated image, the userwill be warned of the gaps and asked if the gaps should be filled. Ifthe user chooses to fill the gap, the software can automatically fillthe gap by selecting a slice image that is substantially in the middleof the gap.

As shown in FIG. 4, in exemplary embodiments, first portion 42 can alsoinclude a “Previously Selected Slice” button 66 and a “Next SelectedSlice” button 68 that allows the user to jump to the next or previousselected slice in the image scan. In exemplary embodiments, the nextselected slice will be a slice that corresponds to a similar time pointduring the R—R cycle, as described above.

Windows 48, 50, 54, 56, 58 can be zoomed in and out, panned to adjustthe size of the image displayed. The zooming and panning can be donesynchronously for all of the windows, or the zooming of each window canbe performed independent of each other.

Referring again to FIG. 2, second screen portion 44 of GUI 40 caninclude an ECG field 70 that displays a patient's ECG signal that wastaken during the imaging of the patient's heart. In most embodiments,only a portion of the entire ECG reading will be displayed on thescreen. Thus, a scroll bar 72 and a zoom bar 74 can allow the user toscroll through the ECG and/or to zoom in and out of the ECG.

The ECG field can be highlighted, typically through a difference incolors or shading from a background of the ECG field, to indicate whichslices are chosen relative to the ECG for inclusion into the projectionimage 50. For ease of reference, the selected slice image that isdisplayed in window 54 will generally have a different shading from theECG field background and the highlighting of the other selected slices.In one exemplary embodiment, the slice displayed in window 54 will beidentified in the ECG field by a light red band 76, and the otherselected slices will be identified by a blue band 78.

In some embodiments, if the user wishes to manually measure the timeinterval of an R—R cycle(s), the user can measure the time intervalbetween two arbitrary or chosen points within the ECG setting oneboundary delimiter by clicking into the ECG and dragging the freeboundary delimiter with a mouse, or other input device, to the secondpoint on the ECG. A field below the ECG can then display the time lengthbetween the two selected points (not shown).

As seen further in FIGS. 2, 4, and 5, information regarding the numberof selected slices, position of the current slice in the ECG (inmilliseconds), and the position of the current slice in millimeters, canbe placed below the ECG field to provide information to the user aboutthe selected slice and ECG.

As the user scrolls through images in the first portion 42, the user canmerely click on the image window 54 to center the ECG cardiac cyclewithin the ECG field so that the user can simultaneously view theselected image slice and its corresponding cardiac cycle. Alternativelyclicking on a portion of a stretched (or normal) reconstructionprojection will display such a slice in window 54 and center thecorresponding ECG signal in the ECG field. Moreover, the user can usescrollbar 72 below the ECG field to scroll through the R—R cycles untilthe selected R—R cycle is displayed within the ECG field. As noted, theselected R—R cycle will be highlighted a different color from the otherselected R—R cycle slices. Also, clicking on the ECG display will selecta slice with its center closest to the point where the user had placed acursor. The slice will be highlighted on the ECG to display the locationof the slice relative to the ECG.

Third screen portion 46 can be configured and sized to display one ormore reconstruction projection images. In exemplary embodiments, thirdscreen portion 46 can display a coronal and a sagittal projection imageof the slices. Alternatively, third screen portion 46 can display only aprojection image that is composed of only the selected slices. Ifdesired, in order to provide a visual impression of the image quality ofthe projection image with only the selected slices 50, a projectionimage having all of the slice image of the image scan 48 can be shownadjacent image 50. Additionally, the third screen portion may only showthe coronal/sagittal projection image having only the selected slices.

Third portion 46 can include a line 80 across the reconstructionprojection image to indicate the position of the slice image that isdisplayed in window 54.

In exemplary embodiments, fourth screen section 52 can be toggledbetween an “ECG” screen 82 (FIGS. 2 and 3) and a “View” screen 84 (FIGS.4 and 5). Once the View tab 83 is activated, a View screen 84 will bedisplayed. View screen 84 includes buttons 86, 88 that allow the user tochange the view of the reconstruction image 50 between a coronal (orMPR3) and a sagittal (or MPR2) projection.

Fourth screen portion 52 can include an ECG tab 90 which when clicked orotherwise selected by the user will display ECG screen 82 so as todisplay information about the average length of the R- cycle for thepatient for certain intervals of the ECG. In some embodiments, the ECGscreen will have a graph which illustrates the duration of the patient'sR—R cycle. Such a graph can graphically illustrate the duration of theR—R cycles, typically in milliseconds. Thus, if the R—R cycle is seen tobe decreasing or increasing over time, the user can modify the method inwhich the slice images are selected.

For example, as shown in FIGS. 2 and 3, the graph 92 shows that the R—Rcycle stays relatively constant through 30 measured R—R cycles. For suchinformation datasets, selecting an absolute time before or after theR-wave will likely be sufficient to select the appropriate slice imagesfor inclusion into the projection reconstruction. If, however, thepatient had graph 94, which shows a change in the duration of R—R cycleover time (e.g., a slope in the graph), it would probably be beneficialto use a percentage of cardiac cycle as the selection criteria for theslices.

Once the user decides on a selection criteria, the user can activateView tab 83 to bring up View screen 84. View Screen will include fieldsthat 96 allow the user to enter their desired selection criteria. ViewScreen 84 can also include an Apply Values button 98 that applies theslice selection criteria for the R—R cycles, a Deselect all Slices 100,Center the ECG image in the ECG field 102 and described more fullybelow.

If the Deselect All Slices button 100 is activated, the slices that wereselected for inclusion in the reconstruction projection image will allbe deselected and the user will be allowed to reselect the slice imagesfor the reconstruction projection, using the slice selection criteriainput into the specified field. Activation of the Center button 102 willcenter the ECG cardiac cycle within the ECG field for the image slicethat is displayed in window 54.

As illustrated in FIG. 6, in order to display a stretched image of thecoronal and/or sagittal reconstruction projection, the user can activatea input box 105 in the fourth screen section. A stretched image allowsexamination as to whether a particular slice fits well with respect toits neighbors, or whether another slice may fit better.

Referring again to FIGS. 4 and 6, checking of a box on the interfacewill provide a stretched coronal or sagittal projection of thereconstruction of slices in third screen section 46. Checking of box 105will make a “Display/Overlay ECG” box 107 active to allow the user tooverlay an ECG signal over the stretched reconstruction projection. Ifdesired, the user can overlay the ECG over the stretched image so as toallow the user to determine if a slice fits well with respect to itsneighbors in a particular cycle, or whether another slice may fitbetter.

The stretched view is needed because the spatial resolution of thecomputer screen/eye combination is not sufficient to adequately view theimage with the necessary detail. Zooming the image would require toolarge a space on the screen for the in-plane dimension, so that theimage is zoomed only along the slice axis and thus appears stretched.

When displaying a stretched image with an overlaid ECG, fourth screenportion 52 can include a “Match” button 113. As shown in FIG. 6,activation of the “Match” function will scale and zoom the stretchedview of the ECG in window 109 to match the portion of the ECG displayedin window 111, the two ECGs being displayed synchronized. In addition,with the click of a button on the input device, the software of thepresent invention can also center the ECG and the stretched view on thecurrent slice, in case it is scrolled out of the field of view.

If the user desires to replace a slice image from the stretched view,the user can scroll through the slices displayed in window 42 until thehighlight marker 76 in the ECG field 70 is over the desired portion ofthe cardiac cycle within field 70. Thereafter, the user can activate theselect slice button 64 to include the slice in the stretched view.

Referring again to FIG. 4, the user can choose to toggle between acoronal projection and a sagittal projection to alter the view of theprojection image by activating the input field 86, 88. In otherembodiments, it may be possible to activate both of fields 86, 88 so asto simultaneously display the coronal and sagittal projections.

The method of using the graphical user interfaces of the presentinvention will now be described. The software of the present inventioncan be a stand alone software package or it can be in the form of aplug-in into a software package, such as a calcium scoring package.First, the user can load an image scan, or a collection of slicesacquired during imaging into the software. The image scan can be a savedimage scan, or alternatively, the image scan can come directly from a CTscanner attached to the computer running the software of the presentinvention.

If available, ECG information that corresponds to the image dataset canalso be downloaded into the software. If an ECG information is notavailable, the software can use the self gating methods described below,to gate the images. If an ECG is loaded into the software, the ECG willbe displayed in ECG field 44 and a composite sagittal/coronal image ofall of the slices of the image scan will be displayed in window 46. Insome embodiments, a center slice of the image set and its two neighborscan be displayed in windows 54, 56, and 58. As can be seen in FIG. 2,the composite image with all of the slices will generally have a jaggedoutline due to the movement of the heart. To improve the selection ofthe slices included in the sagittal/coronal projection, the user canclick on the ECG tab 90 to display the R—R cycle information.

After analyzing the R—R cycle information for any changes in theduration of the R—R cycle during the acquisition period, the user canchoose from a plurality of selection criteria, typically either anabsolute time period or percentage of cycle period. The user can selectthe View tab 83 and enter the selected criteria in the appropriate field96. In some embodiments, if the user selects an absolute time selectioncriteria for a slice, the program will automatically calculate acorresponding percentage of cycle that corresponds to the absolute timeentered by the user for that slice (Window 54). Similarly, if the userselects a percentage of cycle as the selection criteria, the softwarewill automatically calculate and display a corresponding absolute timerelative to the R-wave.

Once the user has entered the selection criteria, the user can activatethe Apply Values button 98 to select the slices for inclusion into theprojection image. As shown in FIG. 2, once the selection criteria valueis applied, the user will be provided with a coronal/sagittal projectionusing only the selected slices in window 50 that is adjacent thecoronal/sagittal projection using all of the selected slices. The ECGwill also be highlighted 76, 78 to illustrate which slices are chosenand the position of the slices relative to the ECG.

FIG. 4 illustrates an coronal image 50 which was selected during thediastole. In contrast, FIG. 5 illustrates the coronal projection image50′ that was selected during systole. As can be seen in the images, thecoronal projection image of the heart during systole is noticeablyblurrier.

If the user desires to re-select the selection criteria, the user canagain click on the View tab 83 and enter a new selection criteria (e.g.,a new time or percentage value) until an acceptable coronal/sagittalprojection image is generated. Advantageously, because thecoronal/sagittal image is updated in real-time when the new slices areselected, the user can tell, in real-time, the effect of the choice ofthe images on the quality of the coronal/sagittal projection image.

Once the user has found an acceptable “global” selection criteria, theuser can manually scroll through the slice images to select or deselectindividual slice images of the image scan to improve the choice of theindividual slice images. For example, as shown in FIG. 2, to scrollthrough the selected slices, the user can activate the Prev. SelectedSlice button 66 and Next Selected Slice Button 68. Such buttons willdisplay in window 54 the Selected slice and in windows 56, 58 the slicesadjacent the selected slice. If the user wants to keep the slicedisplayed in window 54, the user can move to the next slice image bypressing either button 66 or 68. If however, the user wants to selectanother slice, the user can activate the Deselect button 65 and scrollthrough the adjacent slices by activating button 62, 63. Once the userfinds a slice that is acceptable, the user can activate the Selectbutton 64 (FIGS. 4 and 5). The user can repeat this process until all ofthe slices have been selected. Thereafter, the user can save the imagescan (e.g., the selected slices, the sagittal/coronal projection,selection criteria, and the like), and the image of the heart with theselected slices can be calcium scored and/or 3-D rendered. The calciumscoring can be carried out by a separate software program, or it can becarried out by the same program that gated the image scan. Someexemplary computer systems for displaying the GUI of the presentinvention, calcium scoring methods, and software are more fullydescribed in co-pending U.S. patent application Ser. No. 10/096,356,filed Mar. 11, 2002 and U.S. patent application Ser. No. 10/126,463,filed Apr. 18, 2002, entitled “Methods & Software for Improving CoronaryCalcium Scoring Consistency,” (Attorney Docket No. 021106-000710US) thecomplete disclosures of which are incorporated herein by reference.

In another aspect, the present invention provides methods and softwarefor gating an image scan without the use of a gating signal. Because thegating signal (e.g., ECG signal) requires the purchase and use ofadditional expensive hardware and software packages, and requires addedtime for placing the electrodes on the patient and confirming theadequacy of the signal being obtained, it is often desirable to be ableto perform an image scan without the use of a gating signal. Exemplaryself-gating methods of the present invention use information derivedfrom the image slices themselves to infer the heart motion without theuse of an ECG signal.

In one self-gating method, the image slices are selected throughdetection of the size of the heart or pixel intensity in each of theslice images. In another self-gating method, image slices are chosenthrough deriving an average heart rate from the variability of thesignal in the image data and selecting the images based on thecalculated frequency information. In some configurations, a size of theheart is used in conjunction with the frequency measurement to performthe slice selection.

During the quiescent time (e.g., diastole), the heart will be imaged inrelatively motionless and fully expanded size. In contrast, when theheart is in systole, the heart will be contracted. By selecting theimages in which the image of the heart volume is largest, the set ofimages will be selected when the heart is in diastole.

In a first self-gating method illustrated schematically in FIG. 7, thesoftware of the present invention selects slice images from the set ofslices based on the size of the heart. The first step of the firstmethod of self-gating the images is to acquire the set of overlappingimages of the volume of the patient (Step 192). Selection of the imagescan be done successively by depopulating the slice set (based on thesize of the heart in the image) until the necessary number of sliceimages are selected, enough to cover the heart without gaps, whichdepends on slice thickness and heart size. In one exemplary embodiment,depopulating the image scan can be carried out by pairwise comparison.(Step 194). Once the slice images are selected, the coronal/sagittalprojection can be generated and the image of the heart can be calciumscored or 3-D rendered. (Step 196).

If in some of the methods of this invention there are gaps in the imagedata, before saving or calcium scoring the gated image, the user will bewarned of the gaps and asked if the gaps should be filled. If the userchooses to fill the gap, the software can automatically fill the gap byselecting a slice image that is substantially in the middle of the gap.

By drawing on a sagittal or coronal view a region of interest (ROI)encompassing one side of the heart, one can determine the state of theheart muscle by noting the total signal along the line representing theslice, or noting how many pixels have the signal of muscle rather thanthe much lower signal of fat of the lung. When comparing a slice to itsimmediate neighbors, the slice with the most expansion will provide aline with a higher total signal, or with more pixels above a specifiedthreshold, than a slice belonging to a point in time with lessexpansion. For pairwise comparison, each slice is compared to oneneighbor, and the one with most expansion kept. This process can stopwhen a gap would be generated by further depopulation of the slices.

FIG. 8 schematically illustrates another simplified method ofself-gating in which the images are selected by finding the fundamentalfrequency of the heart from the images themselves. The exemplary method200 comprise obtaining a set of overlapping slice images of a volume ofthe patient, typically of the patient's heart. (Step 202). As describedabove in relation to the retrospective gating, the set of images can beobtained with a CT scanner, or an equivalent imaging technology.

The set of images can be run through an algorithm to generate acoronal/sagittal projection of the volume of tissue of the patient.(Step 204). FIGS. 9A and 9B illustrate a coronal and sagittal projectionof an image of a patient's heart. The images have jagged edges due tothe motion of the heart.

The user can then highlight one or more region of the heart in thecoronal/sagittal projection (Step 206). Generally, the user can selectsome region around the jagged outline of the heart. More distinctiveoutlines around the heart will give better results. In exemplaryembodiments, the regions of the heart can be marked with a freehandregion (FIG. 10), a straight line region (FIG. 11). Due to the scannerrotation time, the outline of the heart is generally only selected onone side of the heart outline. It should be appreciated however, thatother conventional marking methodologies can be used to mark a region ofthe image, including the use of automated boundary-finding algorithms.

A pixel intensity signal of the images can be generated by summing thepixel intensities (HU) within the selected region for each slice in adirection that is perpendicular to the slice direction. (Step 208). Theresult of the summation is a signal graph, as illustrated in FIG. 12.The signal graph will produce a plurality of maximas and minimas,wherein each of the maximas generally corresponds to a maximum inflationof the heart. The position along the horizontal axis corresponds to theslice number. The intensity is 0 for slices not included in theselection. The intensities can be corresponded to the slices, each ofwhich is acquired at a certain point in time, usually every 100 ms. Itshould be appreciated however, that the point in time in which the imageacquisition is performed will vary depending on the patient's heart rateor other factors, and such parameters can be set accordingly.

The signal can be analyzed to extract the time information from theimages. (Step 210). Extracting the time information from the signal canbe carried out through an analysis of the frequency spectrum and/orthrough analysis of local intensities of the signal.

In one exemplary method of extracting the time information, a Fouriertransformation is applied to analyze the frequency components of thesignal. In the Fourier transformation, the amplitude profile is viewedas a function of frequency. Each function can be represented through itsFourier components—by combining a number of sine and cosine functions ofdifferent frequencies. The signal intensity profile of the slices willprovide a repetitive maxima and minima. The sinusoid (e.g. sine orcosine function) of the same frequency as the repetitive pattern willhave a large contribution. The goal is to find this principal component,the sinusoid of the corresponding frequency.

The result of the Fourier analysis will be a series of complex numbers.Each number corresponds to a sinusoid of a certain frequency. Theformula is:

${F(k)} = {\frac{1}{M}{\sum\limits_{m = 0}^{M - 1}{{f(m)}{\mathbb{e}}^{\frac{{- 2}\pi\;{imk}}{M}}}}}$where m is the slice number, M is the total number of slices and k isthe coordinate in frequency space (or k-space) and k/M is the frequencywhich corresponds to value F(k),

From the Fourier analysis, information about the magnitude and phase ofthe sinusoid can be obtained. The magnitude indicates the strength ofany one frequency component, including the principal component. For eachcomponent there is corresponding phase information which containsinformation about where that component begins. While the phase cantheoretically be obtained from this phase information, in practice, thephase is changing very fast as a function of frequency, and themeasurement is not reliable.

To find the frequency which is the most dominant portion of thefunction, only the information about the “energy” for each frequencycomponent is necessary. The energy of the sinusoid can be read from thepower spectrum, in which power is defined by:Power(k)=Re(F(k))² +Im(F(k))²where Re is the real part of the complex number F(k) and Im is theimaginary part of the complex number F(k). The result will be a sequencewhich contains only real values. One example of a power spectrum isillustrated in FIG. 14.

After the power spectrum is computed, the Fourier series can be smoothedwith a Gaussian filter to reduce spurious peaks. Because the task offinding the heart beat is circumscribed by physiologic restrictions, thepresent invention can restrict the search for the maximum frequency to arange of approximately 1/2000 ms and 1/500 ms, which corresponds to aninterval of 500 ms to 2 seconds between two heart beats.

Thereafter, the absolute maximum value in the power series and frequencycan be determined. Additionally, the lower and higher frequencies nextto the maximum frequency where the value is half of the maximum valuecan be measured (noted as the half-height interval in FIG. 14). If themaximum frequency and the half-height interval are found, the frequencywhich is directly in the middle of the interval defined by thehalf-heights is used as the “maximum.” If, however, the half-heightinterval can not be determined, the absolute maximum can be used as the“maximum.” From the maximum frequency, the fundamental frequency (e.g.,the heart beat) of the heart can be determined.

From the Fourier transformation, the software can determine thefundamental frequency of the heart and generate images of the heart indifferent phases of the heart cycle. As will be described below, theuser can display a plurality of projection images of the heart, in whicheach of the images corresponds to a different phase of the heart cycle.

Because it is difficult to extract the phase information present in theFourier spectrum, the Fourier transformation does not inform the user asto which slices represent the diastolic phase, systolic phase, and thelike. Moreover, such a transformation does not account for irregularheartbeats or a changing of the heartbeat over the image acquisitionperiod. In order to determine which slices correspond to the diastole,the software of the present invention can analyze the slice images tofind the biggest heart volume image (e.g., the diastole) in which theheart motion is the least.

To determine the phase of each of the slices, (e.g., to determine whichslices correspond to diastole), a local intensity signal of the sliceimages can be run through a derivative filter to produce a graph such asFIG. 13. Generally, this method can be used in conjunction with theresults from Fourier analysis, as described above, to find the size ofthe heart in each of the slice images. With the frequency derived fromFourier analysis and phase from the local maxima, slice selection can beextended beyond the ROI of Step 206. It should be appreciated however,that it may be possible to use the local intensity profile as anindependent algorithm. In such embodiments, the user would need to coverall slices with the selected region of Step 206.

In such an analysis, as illustrated in FIG. 13 each local peak 220 inthe intensity signal corresponds to the maximum inflation of the heart.The peaks can be located through a differential analysis with thedifferential filter in which each peak (i.e., local maximum) has a firstderivative of zero and a second derivative that produces a zero crossingresponse.

From the filtered data, the zero-crossings can be located. A crossingfrom a negative number to a positive and back to a negative correspondsto a maximum. Crossing from a positive to a negative and back to apositive corresponds to a minimum. It should be appreciated however,that the signs of the zero-crossings are dependent on the sign of thesecond derivative filter, which as described above was fixed to benegative-positive-negative. From the zero crossing intervals, thelocation of the maximum intensity values are found and the slices inwhich the heart is in diastole are chosen.

Post-processing of the maxima found above can proceed in several passesover the slice selection. As an initial step, the distance between twoadjacent selected slices will be checked to determine if the slices aretoo close together. In one configuration, the slices will be deemed tobe too close if they are within one third of the heart-rate frequencyfound by the Fourier transformation, this being a reasonable limit forhow much the heart rate may change during the study. It should beappreciated however, that in other configurations, a smaller or largerfrequency distance can be used. If the slices are deemed to be tooclose, the slice that has the lower intensity value will be removed fromthe image set of selected slices.

Next, for each selected slice, the algorithm can resample the images toverify that at least two of the slices' four neighbors are within 30% ofthe heart rate measured by the Fourier analysis so as to avoid irregularspacing. If the slice is outside of the 30% range, the slice will bedeleted from the set of selected slices. It should be appreciatedhowever, that it may be possible to use a criteria different criteria(i.e., smaller or larger than 30% of the heart rate), if desired.

Thereafter, the algorithm can resample the images to check the spacingbetween the remaining slices to see if there are any gaps that arebigger than the slice thickness (which is combination of the thicknessof the slice for a stationary scan and the broadening introduced by thetravel of the patient bed during the helical scan). If there is such agap, the gap can be filled in with a slice of maximum intensity in FIG.13 in the location of the gap. It should be noted, that it is preferableto have the slices be spaced so as not to leave gaps not covered by theslice thickness, as noted above. If there are any slices between twoslices that are within the heart rate found by the Fourier analysis, theslices are deleted from the set of selected slices.

Generally, the derivative filter algorithm will only cover the selectedregion of the scan that was marked by the user. Thus, if the user didnot select the entire image additional slices need to be selected. Ifslices need to be added, a pseudo-selection of slices can be generatedon each end of the selection region. The generated slices will be spacedby the frequency found by the Fourier analysis. A cross-correlation atvarious offsets can be performed to obtain the best estimate of thephase for extension of the frequency information. The offset thatreturns the biggest correlation value is used to extend the dataset tocomplete the image. The same cross-correlation algorithm can be appliedto the pseudo selection slices, as described above.

The computed heart rate can then be used to generate multiple slicesubsets from the original set of slice images, in which each of theslice subsets correspond to a different phase of the heart cycle. (Step212). The present invention can use software to efficiently select asmany sets as there are redundancy, and present them to the user forselection. Multiple selections can be generated from the frequency butat different phases of the cardiac cycle to give the user the choice toselect one. There are (1/frequency*1/time between slices) differentoffsets from the first slice in the original image set. The softwareprogram selects the i^(th) slice as offset+i*(1/frequency*1/time betweenslices) so as to result in 1/frequency*1/time between slices subsets ofthe original scan. The user can choose the desired set from these.

Having the fundamental heart rate, however, is not sufficient for thebest selection of slices since the fundamental heart rate does notexplicitly define which slices correspond to the diastolic phase. Thus,to select the images that were obtained during diastole, the heartfrequency information can be used along with the information obtainedwith the derivative filters to obtain time and phase information togenerate an image in which the heart is at its largest volume (e.g.,diastole). (Step 214).

Additionally or alternatively, the plurality of images of the heart canbe ranked by applying a quality measure so as to rank the images basedon heart size. (Step 216). One quality measure algorithm comprisessumming all of the pixel intensity values over a certain thresholdvalue. The intensity value is normalized by the total number of pixelsin the image to provide the average intensity value of the image.Thereafter, each of the average intensity values of each of the imagesare compared to rank the images relative to each other.

Another quality measure algorithm counts the number of pixels above athreshold value. The number of pixels above the threshold is normalizedby the number of pixels in the image to provide a fraction. The fractioncan identify the percentage of the image that the heart occupies in theimage. Generally, the higher the fraction, the better the selection.Thereafter, the fractions of each of the generated images are comparedand ranked relative to each other. It should be appreciated however,that other quality measure algorithms can be used to rank the images ofthe heart.

Thereafter, the images of the heart can be displayed on a computeroutput display in order of rank so as to allow the user to select thephase most appropriate for the scoring of each vessel within the heart.(Step 218). Alternatively, it is possible for the software toautomatically display only the image with the highest rank.

In some methods, the software of the present invention can be used toauto correlate between image pairs and computes the quality of thecorrelation. Times of slow motion produce better correlations than whenthe motion is rapid. A repetitive pattern can be established from whichthe quiescent times are selected to create the gated image set.Advantageously, the same graphical user interface of FIG. 2 can be usedto gate the image scan.

FIG. 15 illustrates a graphical user interface that can be used toself-gate the set of image slices without the use of an ECG signal. Asshown in FIG. 15, menu toolbar 53 can include additional buttons “Edit,”“Clear Selection,” and “Self Gate” that allows the user to self gate theimage scan. The software allows the user to delineate the regions of theheart where the heart motion can be visually observed.

With the “Edit” button 110, the user can enter an editing/drawing modein which the user can draw a boundary around a region of the image ofthe heart and mark it. The region can be selected by at least twodifferent manners. A first manner is through a straight line selection,in which the user selects a first end point of a straight line and asecond end point of the line to define the region.

In selecting the region, the region must have a minimum length acrossthe slice direction and a maximum length within the direction of oneslice. If the selected region is too small to obtain enough informationfor analysis (e.g., less than about three seconds) or too wide so thatthe signal is lost because of scanner rotation (e.g., more thanapproximately half of the image width), the software of the presentinvention can provide the user with an error message to prompt the userto select a different region and to prevent the computation of aheart-rate from unsuitable data.

In exemplary embodiments, a left click of the mouse defines the firstendpoint, and a right click of the mouse defines the second point. Theline drawn by the user will be used to define a diagonal of arectangular region. In a second manner, the user can use a freehandselection, which allows the user to select a region of arbitrary shape.In one embodiment, the user can depress a “Control” key on a keyboard ofa computer system and move the mouse to draw the region of interest intothe arbitrary shape. Releasing the control key closes the region. Itshould be appreciated however, that the above methods of drawing theregion are merely examples, and other conventional methods ofdrawing/selecting the region can be used.

The region can be a portion of one border of the patient's heart.Advantageously, drawing the region around multiple portions of theborder of the heart allows the user to see and track differentially themotion of the heart through the different portions of the heart cycle.Thus, the user can view the different chambers of the heart as it movesthrough the R—R cycle.

The “Clear Selection” button 112 can delete a region that was previouslymarked by the user. The “Self Gate” button 114 starts the self gatingprocedure that is described herein.

Referring again to FIGS. 10–12, to self gate an image scan, the usermarks selected section(s) in the sagittal view or the coronal view onone side of the heart where the motion can be seen. Motion of the heartwill be shown by the jagged edge of the heart in the sagittal image andcoronal image. Straight line boundaries 118 (FIG. 11) or freehandboundaries 120 (FIG. 10) can be drawn on one or more portions of an edgeof the heart. If desired, the user can select multiple regions.

Once the regions have been selected, the user can click on the Self Gatebutton 114. The self gate software can them compute the averagefrequency of the heart beat using the information of the selected regionand generate a number of selection. FIG. 16 schematically illustrates anexemplary data flow of the present invention.

FIG. 17 shows one preview screen graphical interface for displaying themultiple selections. One selection represents the biggest heart volumebased on the frequency information of the selected region and theintensity values in the marked regions. The other selections are basedonly on the frequency information. Each selection corresponds to adifferent phase of the measured heart frequency.

As shown in FIG. 17, the preview screen 129 includes a main previewwindow 130 having the current selection. The default selection isderived from the selection that includes the intensity and frequencyinformation. A smaller image 132 of the current selection can also bedisplayed alongside the right portion of the graphical user interface inone of the small preview windows and can be framed by colored frame 134.Clicking or otherwise selecting on another image alongside the smallpreview windows (e.g., the right portion of the graphical userinterface) will display the selected image on the main preview window.The topmost image 132 shows the selection inferred by intensity andfrequency information derived from the image scan. The remaining imagesshow selections that use only the computed heart frequency at differentoffsets (e.g., different phases of the heart's motion). As seen in FIG.17, many of the images at the different phase of the heart hasnoticeable blurring due to the motion of the heart. Nonetheless,providing a plurality of images of the heart in different phases allowsthe user to visually determine which heart image is best.

The user can select different projection of the current preview byactivating the Axial button 136, Coronal button 138, or Sagittal button140. The slider 142 can be activated by the user to scroll through theslice projections, if desired. When the user finds a projection imagethat is acceptable, the user can click on the OK button 144, which willapply the current selection and return to the main screen of thegraphical user interface (FIG. 2).

As described above, once the selected image set is deemed acceptable,the image set can be calcium scored and saved. Before saving the slicesas a new DICOM series, the selection of images can be checked for gaps.If there are gaps, the number of gaps can be reported to the user withtheir size range. The user can then select to ignore the gaps or canelect to fill in the gaps that are bigger than a specified threshold,which the user can specify.

One method of filling in the gaps is with a slice closest to the middlepoint between the selected slices. Of course, these gaps may also befilled through low order interpolation algorithms such as nearestneighbor, and in increasing order, linear, cubic and so on, or Fourierinterpolation.

In another aspect, the present invention provides improved methods andsoftware for calcium scoring the images. Retrospective gating oftencauses mismatches between the scanner rotation and the heart rate.Consequently, the selected images may not always be equally spaced suchthat there are gaps between the images. Most calcium scoring algorithms,however, are based on algorithms that require a fixed spacing betweenthe slice images.

Unfortunately, conventional linear or other low order interpolationschemes that can be used to generate equally spaced slice images fromthe selected merely blur the images, which degrades the calcium scoringof the images. The present invention provides a Fourier Interpolationthat can rescale the dimensions of the image slices that does notintroduce blurring or degrade the resolution. A more completedescription of Fourier Interpolation can be found in U.S. Pat. Nos.4,908,573 and 5,036,281 and in Kramer D. M., Li A, Simovsky I, HawryszkoC, Hale J and Kaufman L., “Applications of Voxel Shifting in MagneticResonance Imaging,” Invest Radiol 25:1305, 1990, the completedisclosures of which are incorporated herein by reference.

While all the above is a complete description of the preferredembodiments of the inventions, various alternatives, modifications, andequivalents may be used. Although the foregoing invention has beendescribed in detail for purposes of clarity of understanding, it will beobvious that certain modifications may be practiced within the scope ofthe appended claims.

1. A method of Fourier gating an image dataset, the method comprising: obtaining a plurality of overlapping slice images of a heart; calculating an intensity signal for the overlapping slice images; Fourier transforming the intensity signal to find a fundamental frequency of a cycle of the heart; analyzing the intensity signal with a derivative filter to locate slice images that were obtained during diastole of the heart cycle; and selecting slices that correspond to the diastole.
 2. The method of claim 1 wherein Fourier transforming further comprises: computing a power spectrum from a Fourier series transformation; smoothing the Fourier series with a Gaussian filter; and computing a maximum frequency from the power spectrum, wherein the maximum frequency corresponds to the fundamental frequency.
 3. The method of claim 2 comprising restricting a search of the fundamental frequency range to be between 1/2000 ms and 1/500 ms.
 4. The method of claim 1 wherein Fourier transforming further comprises: computing a power spectrum from a Fourier series transformation; and computing a maximum frequency from the power spectrum, wherein the maximum frequency corresponds to the fundamental frequency.
 5. The method of claim 1 further comprising generating and displaying a plurality of projections of groups of slice images, wherein each of the groups of slice images correspond to the heart in different phases of the heart cycle.
 6. The method of claim 5 comprising ranking the groups of slice images based on heart size in the projection.
 7. The method of claim 6 wherein ranking comprises applying at least one quality measure to each of the groups of slices.
 8. The method of claim 1 comprising resampling the selected slices to substantially equilize the spacing between the selected slices.
 9. The method of claim 1 comprising filling in gaps between the selected slices through selection of a slice closest to a center of a nearest two slices spanning the gap.
 10. The method of claim 1 comprising filling in gaps between the selected slices through linear interpolation of a nearest two slices spanning the gap.
 11. The method of claim 1 comprising filling in gaps between the selected slices through high order interpolation of slices spanning the gap.
 12. The method of claim 1 comprising filling in a gap between the selected slices by applying a Fourier interpolation to generate a set of needed images.
 13. A method of Fourier gating an image dataset, the method comprising: obtaining a plurality of overlapping slice images of a heart; generating at least one of a coronal and sagittal projection with the set of slice images; receiving input identifying a marked region of the projection; calculating an intensity signal along a direction of the slice images for the projection in the marked region; Fourier transforming the intensity signal to find a fundamental frequency of a cycle of the heart; analyzing the intensity signal with a derivative filter to locate slice images that were obtained during a diastole of the heart cycle; using the intensity signal analysis to establish the phase of the fundamental frequency obtained from the Fourier transformation of the heart motion; extending the selection process outside the marked region by obtaining the frequency of the heart motion from the Fourier transformation and the phase from the intensity signal; and selecting slices that correspond to the diastole.
 14. A method of Fourier gating an image dataset, the method comprising: obtaining a plurality of overlapping slice images of a heart; generating at least one of a coronal and sagittal projection with the set of slice images; receiving input identifying a marked region of the projection; calculating an intensity signal along a direction of the slice for the projection of the overlapping slice images within the marked region; Fourier transforming the intensity signal to find a fundamental frequency of a cycle of the heart; obtaining a principal component of a Fourier spectrum within an allowed frequency window; forming data sets of slices separated by a time interval that substantially corresponds to the principal component; and presenting a projection image formed from the data sets for an operator to select a set for further processing.
 15. The method of claim 14 wherein further data processing is coronary calcium scoring.
 16. The method of claim 14 wherein the further processing is 3-D volume rendering.
 17. The method of claim 14 wherein presenting comprises ranking each data set by a size of the heart within the marked region and visually indicating to the operator the ranking in the presentation.
 18. A method of self-gating a set of images, the method comprising: acquiring a set of overlapping slice images of a heart; generating a projection with the set of slice images; receiving information identifying a marked region of the projection; analyzing the marked region to calculate a heart frequency and a phase of motion of the heart, the analyzing comprising summing an intensity value along a slice direction of a region of the projection of each slice set that was marked, and Fourier transforming the intensity value to generate Fourier components in frequency space; selecting groups of slice images from the set of slice images, based on their relative position in the calculated heart motion frequency and phase; and generating a plurality of groups of slices that correspond to different phases of heart motion.
 19. The method of claim 18 comprising computing a frequency power spectrum from the Fourier components.
 20. The method of claim 19 comprising finding a maximum value of the frequency power spectrum of the heart motion.
 21. The method of claim 20 comprising smoothing the frequency power spectrum of the heart motion.
 22. The method of claim 20 comprising taking a middle point of a half-height interval of the maximum value of the frequency power spectrum of the heart motion.
 23. The method of claim 20 comprising limiting the frequency to a range between 1/2000 ms and 1/500 ms.
 24. The method of claim 18 comprising measuring a size of the heart in a marked region of the set of slice images.
 25. The method of claim 24 wherein measuring comprises applying a derivative filter to measure a local intensity signal derived from the marked region of the slice images.
 26. The method of claim 18 comprising: obtaining a projection image from each set of selected slice images, each representing a phase of the heart motion; displaying the group of projections of the heart; and highlighting the projection image of the heart in which the marked region of the heart has its largest size.
 27. The method of claim 26 wherein highlighting comprises displaying the projection image of the heart in which the marked region of the heart has its largest size as a larger image.
 28. The method of claim 26 wherein highlighting comprises marking by a ranking number the projection of the heart in which the marked area of the heart has its largest size.
 29. The method of claim 18 comprising: selecting a set of slices of the heart on the basis of a preferred projection of the set of slices; and calcium scoring the selected set of slices of the heart.
 30. The method of claim 18 comprising: selecting a set of slices of the heart on the basis of a preferred projection of the set of slices; and 3-D rendering the set of slices of the heart.
 31. The method of claim 18 comprising verifying that the marked region contains enough information to compute the frequency and phase.
 32. The method of claim 31 where verifying comprises computing that at least 3 seconds of data were included in the marked region.
 33. The method of claim 31 where verifying comprises computing that the marked region of the heart does not extend further than half of the field of view.
 34. The method of claim 18 comprising limiting the frequency to a range between 1/2000 ms and 1/500 ms.
 35. The method of claim 18 comprising ranking the groups of slices.
 36. The method of claim 35 comprising displaying the projection images of the selected slice sets in order based on their ranking.
 37. The method of claim 35 wherein ranking comprises applying at least one quality measure to each of the groups of slices, wherein each of the groups of slices is used to generate a projection image.
 38. The method of claim 18 wherein the set of images are CT images.
 39. The method of claim 18 wherein the marked region comprises a region selected along a border of the heart.
 40. The method of claim 18 comprising filling in any gaps in the groups of slice images.
 41. The method of claim 40 comprising re-sampling the selected slice images to provide approximately equally spaced slice images in each group of slice images.
 42. The method of claim 40 wherein filling in any gaps comprises applying a Fourier interpolation to generate a set of needed images.
 43. The method of claim 40 wherein filling in any gaps comprises applying a nearest neighbor interpolation to generate a set of needed images.
 44. The method of claim 40 wherein filling in any gaps comprises applying a linear interpolation to generate a set of needed images.
 45. The method of claim 40 wherein filling in any gaps comprises applying a high order interpolation to generate a set of needed images.
 46. The method of claim 18 wherein the selected groups of slice images comprise slice images that substantially cover the heart without gaps and are substantially non-overlapping.
 47. A method of self-gating a set of images, the method comprising: acquiring a set of overlapping slice images of a heart; generating a projection with the set of slice images; receiving input identifying a marked region of the projection; analyzing the marked region to calculate a heart frequency and a phase of motion of the heart; selecting groups of slice images from the set of slice images, based on their relative position in the calculated heart motion frequency and phase; generating a plurality of groups of slices that correspond to different phases of heart motion; and ranking the groups of slices by applying at least one quality measure to each of the groups of slices, wherein each of the groups of slices is used to generate a projection image, wherein applying the quality measure comprises: in a marked region of the projection image of the slices of the heart, summing pixel intensity values over a certain threshold value for each of the lines representing a slice in the projection images of the slices in each of the groups; normalizing the pixel intensity values by a total number of pixels in the projection images to provide an average intensity value for the slices in each of the groups; and comparing the average intensity values of each of groups and ranking the groups based on the average intensity value.
 48. A method of self-gating a set of images, the method comprising: acquiring a set of overlapping slice images of a heart; generating a projection with the set of slice images; receiving input identifying a marked region of the projection; analyzing the marked region to calculate a heart frequency and a phase of motion of the heart; selecting groups of slice images from the set of slice images, based on their relative position in the calculated heart motion frequency and phase; generating a plurality of groups of slices that correspond to different phases of heart motion; and ranking the groups of slices by applying at least one quality measure to each of the groups of slices, wherein each of the groups of slices is used to generate a projection image, wherein applying the quality measure comprises: in a marked region of the projection image of the heart, summing pixel intensity values for each of the lines representing a slice in the projection images of the slices in each of the groups; and comparing the summed intensity values of each of groups and ranking the groups based on the summed intensity value.
 49. A method of self-gating a set of images, the method comprising: acquiring a set of overlapping slice images of a heart; generating a projection with the set of slice images; receiving input identifying a marked region of the projection; analyzing the marked region to calculate a heart frequency and a phase of motion of the heart; selecting groups of slice images from the set of slice images, based on their relative position in the calculated heart frequency and phase; generating a plurality of groups of slices that correspond to different phases of heart motion; and ranking the groups of slices by applying at least one quality measure to each of the groups of slices, wherein each of the groups of slices is used to generate a projection image, wherein applying the quality measure comprises: in a marked region of the projection image of the slices of the heart counting the number of pixels in each of the lines representing a slice in the slices in each of the groups that is above a pixel intensity threshold; normalizing the counted number of pixels that are above the pixel intensity by dividing the counted number of pixels by a total number of pixels in the slices in the group; comparing the normalized number of each group of slice images; and ranking the groups of slice images using the comparison of normalized numbers.
 50. A method of self-gating a set of images, the method comprising: acquiring a set of overlapping slice images of a heart; generating a projection with the set of slice images; receiving input identifying a marked region of the projection; analyzing the marked region to calculate a heart frequency and a phase of motion of the heart; selecting groups of slice images from the set of slice images, based on their relative position in the calculated heart motion frequency and phase; generating a plurality of groups of slices that correspond to different phases of heart motion; and ranking the groups of slices by applying at least one quality measure to each of the groups of slices, wherein each of the groups of slices is used to generate a projection image, wherein applying the quality measure comprises: in a marked region of the projection image of the slices of the heart counting the number of pixels in each of the lines representing a slice in the slices in each of the groups that is above a pixel intensity threshold; comparing the counted number of each group of slice images; and ranking the groups of slice images using the comparison of counted numbers. 